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All About R Programming Language

Whenever you come across powerful statistics, analytics, and visualizations that are used by business leaders, researchers, and data scientists, chances are R Programming Language is behind them. Don’t know much about R? Well, we got you covered. This blog talks about everything you need to know about R, from what it is and when it was created to whether it’s popular and what companies use R. So if you’re up for a deep dive into R, read in full.

What is R?

R is basically an open-source programming language created by statisticians for statisticians. While other languages are general-purpose, R Programming Language is known specifically to help with statistical computing and data visualization and is used by data analysts, scientists, and data scientists. However, you should know one thing R is not just a programming language. It’s also an environment for the users who wish to perform statistical analysis & modeling but don’t have programming skills.

What Falls Under Basic and Advanced R Programming?

Similar to other programming languages, R is also divided into parts: basic and advanced R. Here’s what falls under these parts:

Basic R

Basic R, as the name tells, includes basic knowledge of R Programming Language. It includes writing R scripts for practical applications, the core of R, and data manipulation. If you’re fluent in Basic R, you can easily:

• Produce data plots of different types.


• Perform data manipulation.


• Create descriptive statistics.


• Create simple functions.


• Conduct specification test and multiple linear regression analysis.


• Work with different data structures and data types such as list, matrix, data frame, etc.

Advanced R

Advanced R Programming Language includes more in-depth concepts. This part of R includes efficient data manipulation, advanced plotting, and writing efficient scripts to be able to solve complex applications. Advanced R also includes the below concepts:

• Return Values


• Parameters


• Debugging


• Variable Scope


• Data extraction


• Advanced R graphics (ggplot2)


• Advanced-Data Manipulation


• Several Useful Packages

 Mastering Advanced R will allow you to:

• Write complex R functions.


• Perform advanced data manipulation like merging or reshaping the data.


• Use Advanced Plot Package.


• Perform data analysis on all types of data.

Who uses R?

Finance Companies

The finance industry actively makes use of data science. And guess what the best tool/language for data science is? It’s R-programming language. R offers finance companies a suite of statistical functionalities that they can use to carry out different tasks such as adjusting risk performance and performing visualizations such as: 

• Drawdown Plots


• Density Plots 


• Candlestick Charts


• & More

Research Institutes

Several research institutions, such as agricultural universities, and educational institutes teaching political science, are actively shifting from SPSS to R for analyzing data. Even universities such as the University of California and Cornell University teach their students to R for effective data analysis and crafting visualizations.

Banks

Banks, similar to financial companies, actively use R for risk analytics such as credit risk modeling. Also, R is used along with Hadoop to analyze customer retention, and quality. What banks use R, you may think? Well, Bank of America uses R to analyze financial losses and for financial reporting.

Healthcare Companies

Several companies that operate in the epidemiology, drug discovery, bioinformatics, and genetics domain make use of R. Such companies, with the help of R, crunch tones of data which makes data analysis a piece of cake. Also, R is used by companies who work to develop drugs for analyzing drug safety data and performing pre-clinical trials. What’s more, the Bioconductor Package of R offers numerous functionalities using which scientists can carefully analyze the genomic data. Last but not least, data scientists in the epidemiology domain use R to extensively analyze and predict the spread of diseases. 

Social Media Companies 

Social media has always been data intensive. Millions, probably billions of users, scroll Facebook, Instagram, and Twitter feeds each day. And based on their data or preferences, they’re shown ads, or their user experience is modified. And all this is made easy with R-programming language.

Using R, several social media companies, including Facebook, analyze user sentiments to enhance the overall UX. You can even find several tutorials for analyzing Facebook comments and other data on the internet. SocialMediaMineR is an R-based tool that consumes one or more URLs and returns the info on the popularity of every URL on the internet.

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